This paper has previously appeared in the
November/December 2010 issue of D-Lib Magazine (http://www.dlib.org).

Abstract

We propose a framework for organizing
multiple metadata specifications in a container that can be
handled as a whole. This framework, named Information for
Learning Object eXchange (ILOX), is developed as part of the IMS
Learning Object Discovery & Exchange (LODE) specification
that aims to facilitate the discovery and retrieval of learning
objects stored across more than one collection. While thus far
ILOX has been demonstrated to resolve a number of challenges
specific to the e-learning domain, it is a generic framework that
can be profiled to organize metadata about any type of digital
content.

Introduction

Learning objects are digital resources used for
teaching, learning, or training. Like other types of digital
content, metadata (i.e., machine-readable descriptions of
learning objects) are used to provide the information necessary
to search for learning objects, assess their usefulness, and
retrieve them.

There are many ways to
look at a learning object. One might be interested in its
pedagogical, technical or legal aspects. One might want to know
how it is used in practice, how its users perceive it or how
accessible it is to people with special needs. All these aspects
are important and have to be taken into account in order to
efficiently find, retrieve and reuse a learning object. A variety
of metadata specifications exist that capture different aspects
of learning objects. Some general purpose specifications such as
IEEE Learning Object Metadata [1] and Dublin Core education [2]
capture the main aspects of learning resources, whereas
specialized metadata schemes permit one to produce detailed
descriptions of a particular aspect of a learning object (e.g.,
IMS Accessibility For All [3] and Contextual Attention Metadata
[4], which enables descriptions of the accessibility of a
resource and its actual usage1,
respectively).

Collecting and organizing
all the information available about a learning object is
difficult. One can either keep the various metadata elements in
separate documents that reference each other or create ad hoc
metadata profiles that combine relevant pieces from various
specifications. None of these solutions is entirely satisfying.
In practice, references between metadata records prove difficult
to maintain and process while ad hoc profiles are usually defined
within limited communities outside of which they are not
interoperable. Moreover, these patchworks are generally difficult
to create, understand, and
maintain.

The IMS Learning Object
Discovery & Exchange (LODE) [5] specification aims to
facilitate the discovery and retrieval of learning objects stored
across more than one collection. It can be seen as a glue
specification that profiles existing general-purpose
specifications in order to take into account requirements
specific to the educational domain, rather than creating new
specifications. Among other things, it proposes a framework,
named Information for Learning Object eXchange (ILOX), for
organizing multiple metadata specifications in a container that
can be handled as a whole.

Note that, although initially addressing
problems faced by the e-learning community, ILOX is a generic
framework that can be profiled to organize metadata about any
type of digital content and is not limited at all to metadata
about learning objects.

This paper is an introduction to ILOX. Section
2 describes how the conceptual model of ILOX combines the
Functional Requirements for Bibliographic Records (FRBR) data
model [6] with a powerful abstraction mechanism named
materialization [7] to organize metadata records. Section 3
presents the application profile of ILOX used by the Learning
Resource Exchange, a service that allows European teachers to get
access to digital educational content from many different
countries and providers [10].

Modeling Learning Objects with FRBR

In information modeling2, materialization [7] is used to represent the
relationship between a class of categories (e.g., learning
objects) and a class of more concrete items (e.g., learning
object copies). Materialization is important in formulating
metadata for learning objects, because it captures commonalities
between descriptions of objects at different levels of
generality: metadata attributes may apply at a more abstract
level, to a larger number of instances, or at a more concrete
level, to a smaller number of
instances.

Figure 1 – learning objects have multiple copies.

The class diagram of Figure 1 presents an
example of materialization. It relates a more abstract class:
Learning Object to a more concrete one: LO Copy. Class Learning
Object represents the information about learning objects (e.g.,
their titles, their descriptions) whereas class LO Copy
represents the information about concrete copies of these
learning objects (e.g., the file names and path of these LO
copies). Materialization is noted as a straight line with a * at
its more concrete class end.

The attributes of abstract classes are
propagated to the classes materializing them. So if a learning
object has the title "Hamlet", then all LO Copies materializing
it also have the title "Hamlet". This allows us to express
metadata economically: we need only to define title once for a
learning object, rather than repeating it for each LO
Copy.

Materialization provides a powerful mechanism
to structure metadata descriptions. In the bibliographical
domain, the Functional Requirements for Bibliographic Records or
FRBR [6] can be modeled as a materialization hierarchy that is
useful for distinguishing between aspects of learning objects
relevant to different contexts. The FRBR concepts of "work",
"expression", "manifestation", and "item" as they relate to
learning objects are illustrated in Figure
2.

Figure 2 - Example of different FRBR expressions,
manifestations, and items of a learning object work.

A FRBR "work" is a distinct (intellectual or
artistic) creation, such as the learning object about nutrition
shown on the example of Figure 2. Different versions of this
learning object can exist: for example, an English and a French
version. These versions are different FRBR "expressions" of the
work. Each version of the learning object can take different
forms. For example, the English version of the learning object
about nutrition can be available as a preview, an IMS Content
Package and an IMS Common Cartridge. Each of these different
embodiments of an expression of a work is referred to as a FRBR
"manifestation". Finally, copies of the IMS Common Cartridge of
the English version of the learning object may exist in a number
of locations. Each of these copies is a FRBR
"item".

Figure 3 – Using materialization to model the
relationship between the different FRBR representations of
learning objects.

As depicted in the class diagram of Figure 3,
materialization can be used to model the relationships between
different FRBR aspects of learning objects. Class LO Copy models
the item aspect of learning objects. Class LO Copy is the
materialization of class LO Package, which models their
manifestation aspects. In turn, class LO Package is the
materialization of class LO Version, which models the expression
aspects of learning objects. Finally, Class LO Version is the
materialization of class Learning Object, which models the work
aspect of learning objects. To save space, each of these four
classes in the example is shown with only two attributes typical
of the aspect that it models.

The ILOX data model structures a learning
object description as a materialization hierarchy such as the one
presented in Figure 3. The FRBR materialization levels are used
as follows:

Work is an abstract view of a learning object
that captures the commonalities between all the possible
variations of this learning object such as, for example, the
pedagogical content that is common across all the variations of
the learning object.

Expressions are used to capture information specific to
the different versions, drafts, translations, and localizations
of learning objects, such as
language.

Manifestations are
used to capture information specific to the way a given
expression of a learning object is encoded and presented, such as
file formats.

Items are used to capture information specific to
the concrete copies of learning objects, such as the URI where
they can be accessed.

Some types of information will typically be
specific to one FRBR materialization level. For instance, the
language of an object is typically characteristic of an
Expression: an object may be translated into a different language
without becoming a different Work, but different Manifestations
of the same Expression are all expected to be in the same
language. However, other types of information may appear at
multiple materialization levels: access rights may apply to all
copies of a Work, or may be specific to a particular
Manifestation (e.g., a preview of the learning object vs. the
runtime object). The same information at a lower materialization
level overrides information appearing at a higher level. (So
access rights can be set for the Work as a whole, but access
rights for a specific Manifestation can be treated as an
exception.)

An ILOX instance can be rooted at any level of
the hierarchy depending on how abstract or concrete one needs to
be. Handling learning object descriptions at
the:

Work level permits one entry per learning object
with no immediate distinction between learning object
versions;

Expression level permits one entry per learning object
version with no immediate distinction between the different
formats of a given learning object version, and without having to
decide which Work different Expressions belong
to;

Manifestation level
permits one entry per learning object format with no immediate
distinction between the different copies of a learning object,
and without having to decide which Work or Expression the
Manifestations belong to;

Item level permits one entry per learning object
copy, without having to decide which Work, Expression or
Manifestation the Items belong
to.

Figure 4 – Pattern for describing the different
FRBR aspects of a learning object.

At each level of the hierarchy, a common
pattern is used to model the corresponding FRBR aspect of the
learning object. This pattern is shown on the class diagram of
Figure 4 where a given FRBR level (modeled by class "LO at FRBR
level #n" is described by:

Descriptions” are used to describe each
FRBR level of a learning object with level-specific metadata.
They consist of two components:

facet indicates what “facet” of the
given FRBR aspectÂ of the learning object in question is
described, and

metadata contains a metadata description of the
given FRBR aspectÂ of the learning object in
question.

Each level can have multiple metadata
descriptions, each with its own facet to differentiate between
them. ILOX does not define a controlled vocabulary for facets.
Instead, application profiles of LODE are expected to select
controlled vocabularies for the facet elements. These
vocabularies generally differ from one application profile to
another and from one FRBR level to
another.

The Learning Resource Exchange and its
Metadata Application Profile

The European based Learning Resource Exchange
(LRE – http://lre.eun.org/) federates metadata
from a variety of learning object repositories and provides a
service allowing teachers to access the learning objects from
various access points. Potentially, any application that utilizes
learning objects can connect to it. European Ministries of
Education make learning objects accessible for their own teachers
via national portals. When learning objects have the potential to
'travel well' for use in contexts beyond their national origin,
content providers describe them with metadata using the LRE
Metadata Application Profile [10] and expose this metadata so
that it can be easily accessed by the LRE. In turn, the LRE
compiles the collected metadata to produce a digital catalog of
learning resources that can be consulted by teachers using the
LRE or their own national portals.

In the LRE, obtaining a learning object is a
three-step process:

The first step involves discovering and
evaluating metadata in order to select a learning object that
meets a user's need.

The second step is negotiating access to the
selected learning object. This step can require authentication,
authorization, and encryption schemes depending on the learning
object level of protection [11]. For learning objects that are
freely available at the specified location, the negotiation step
is perfunctory.

The third step is retrieving the selected
learning object at the location obtained during the second
step.

Controlled vocabularies describing the
pedagogical qualities of the learning objects such as learning
resource type, subject, typical age range and learning contexts
(among others), translated into 24 languages, are integrated in
the LRE Metadata Application Profile (LRE MAP). The vocabularies
are managed and made accessible using a browsable interface and
for machine-to-machine processing in the Vocabulary Bank for
Education.

Federating sets of
metadata coming from various origins, with content provided by
ministries of education (MoE), commercial and non-profit content
providers, and cultural heritage organizations poses a number of
challenges. One of the more pressing needs for the LRE in
federating metadata is to overcome the limitations of a reliance
on a single metadata specification such as IEEE LOM without
undermining interoperability and backward compatibility as needs
and requirements continue to evolve. Furthermore, a rapid rise in
the production and dissemination of complex learning objects (in
multiple languages, in multiple formats, in multiple locations,
tailored for particular populations and dedicated platforms)
necessitates a more precise way to indicate which aspect of the
object is being described in a single metadata record. Finally,
the generation of metadata about learning objects is no longer
within the strict purview of the objects’ creators and
trained indexers. The ascent of social networking cultures has
created opportunities and expectations that users and networked
communities of practice will generate and trust social metadata
to guide their choices about services and products; including
learning objects. Such user-generated comments, bookmarks and
other types of evaluations are producing valuable streams of
information for building recommendation systems, structuring
search result rankings and feedback channels for content creators. All participants in the
LRE federation (i.e., users, content providers, and portal
managers) benefit if such social data can be captured, aggregated
and transported in a single metadata container with all relevant
available information about a learning object for use in multiple
contexts. Current metadata specifications used in the e-learning
domain such as Dublin Core and IEEE LOM do not allow for the
capture, aggregation and dissemination of social metadata without
undermining interoperability. The following scenario describing
the types of learning object metadata managed by the LRE vividly
demonstrates the challenges of metadata management in the
e-learning domain:

A metadata record for a learning object,
“Resistance in a Wire” is cataloged by the LRE from a
harvest using OAI-PMH protocol. The creators of this learning
object licensed it under a Creative Commons license allowing for
its reuse and sharing with proper attribution. The object, a
simulation allowing users to manipulate a wire’s
resistivity along with activities and lesson plans is available
in three languages, English, French and Spanish. The learning
object’s versions are available in several formats. While
the English version can be rendered in a web browser it also
comes packaged as an IMS Common Cartridge version 1.1, which has
a more restrictive license than the web-based format. The French
and Spanish versions are available only as IMS Common Cartridges
and access to them resides behind a login wall. The IMS Cartridge
format of the English version has been rated and bookmarked by
several hundred teachers who have used it. Download statistics
have been collected when the object packaged as an IMS Common
Cartridge has been downloaded in English, French and Spanish.
Knowing the language version of an object may not be enough in
the European context with a variety of educational systems and
curriculums. The same learning object in French is also tailored
for the French educational system. There is also a Swiss system
version. Finally, the English version that can be rendered in a
web browser also allows for setting to make the object available
for visually impaired learners.

The challenge is to describe all this
information in one metadata record and provide users with an
ability to discover the version and format of this learning
object that meets their needs and to evaluate the object’s
suitability with the help of recommendation
systems.

IMS LODE Information for Learning Object
eXchange specification (ILOX) in combination with the IEEE LOM
Metadata standard (LOM) [1] has been selected as the basis for
the Learning Resource Exchange Metadata Application Profile v4.5
[10] because it can address the evolving requirements of a
learning object repository federation by providing for
interoperability of metadata, the ability to identify what is
being described by metadata and the use of multiple metadata
specifications in one metadata record.

As illustrated on Figure 5, the main
commonalities shared by all subsequent levels of this learning
object will be described with an IEEE LOM metadata instance
attached at the ‘main’ facet of the root level (in
the LRE MAP, the Work level is the preferred root level). The LOM
will include general elements such as title, description and
keywords as well as pedagogically relevant elements such as
learning resource type, age range for typical users, intended
educational context, etc.

Figure 5 – Describing the “main”
commonalities shared by all FRBR levels using IEEE LOM at the
ILOX Work level.

A license/rights facet is available for use at
this (and every) level. We can use the license/rights facet to
attach metadata stipulating the Creative Commons license terms.
More restrictive license terms for versions and manifestations at
the lower level of the ILOX will have their own license/rights
metadata attached and the license stipulations of the more
abstract level will be superseded by the license information at
the more concrete levels. For the Spanish and French versions
available as IMS Common Cartridge with a restrictive license, we
would attach the rights information at the Manifestation
level.

Furthermore, because the copies of the IMS
Common Cartridge format of the French and Spanish versions are
behind a login wall, a transaction facet will be attached at the
Item level to indicate the steps necessary for negotiating access
to the retrievable copy of the object. (To meet these
requirements, the LRE has developed an Access Control Metadata
Schema that must be attached at the “transaction”
extension point [11].)

The ILOX Expression Dimension type provides
solutions to make explicit the relationship between the versions,
their formats and ultimately the location where these items are
available for retrieval. Using the Expression Dimension Type
“language” we can indicate that the object is
available in French, English and Spanish. We can also use the
“coverage” Dimension Type to indicate when the
object’s version has been tailored to meet the needs of a
particular region, which differentiates it from versions that are
in the same language but that are intended for another
educational system. For each Expression of the learning object a
Manifestation is mandatory. The LRE uses controlled vocabularies
for Manifestation names such as “thumbnail”,
“experience” (a web page), “preview” as
well as “package in” for objects that are packaged in
some form. In this scenario the Manifestation name is
“package in” (an IMS Common Cartridge v1.1) and
“experience” for objects that play directly in the
browser (in this case only for the English version of the
learning object).

There are two ways to express information about
the accessibility features of the learning object the first way
is to indicate accessibility as a versioning of the object.
Another way is to attach metadata describing the accessibility
features of the object at the ILOX Expression level. In the case
of the learning object described above, by using the facet
mechanism at the Expression level we can indicate that the
English version of the object also offers features tailored for
visually impaired learners by attaching metadata at the
“accessibility” facet describing the options
available. This illustrates how ILOX allows for taking advantage
of standard schema such as “IMS Access for All” [3]
for addressing specific requirements.

The LRE Metadata Application Profile also
provides for the use of a ‘reputation’ facet at any
level to capture any type of user generated assessments of a
learning object (ratings, annotations, bookmarks) that can aid in
the object’s retrieval and rankings, work with
recommendation systems and/or support social navigation tools.
Ratings and comments made about the English version available in
the web browser can be attached as metadata at any level and
provided to the national portals where the ratings can be used to
sort results for most popular learning objects or to let teachers
browse objects that have been rated or vetted by fellow teachers.
A schema to support these requirements is in development by an
expert team of the CEN Workshop on Learning Technologies
[12].

Using the paradata facet we can capture and
aggregate information produced by recording meaningful actions
and processes users initiate to locate and access the learning
object in this scenario (e.g., web server logs). Such data
includes number of visits, number of downloads, etc. This data is
initially collected at the item level and then can be aggregated
at different upper ILOX levels using the paradata facet. Such
aggregation is intended to track the number of times different
formats of different versions of an object were accessed,
starting from the number of downloads of individual copies at the
Item level. Aggregations will be available at each level for
exchange and sharing. For example, the number of downloads of an
object can be collected for each item and then aggregated by
format (Manifestation), i.e. 10,000 downloads for all Common
Cartridge formats and 15,000 times played in a web browser and
then aggregated at the Expression level to track version
preferences. This information can be offered to the content
provider as feedback to understand user preferences in different
national contexts and with different
formats.

Thus, using ILOX in combination with LOM and
other metadata specifications makes it possible to organize all
these specifications in one metadata container. Using level
specific attributes at the ILOX Expression and Manifestation
levels makes it possible to provide information on the ways
versions differ from one another and then provides information
allowing for the efficient retrieval of those versions in all
their available formats and locations. The facet mechanisms of
the ILOX allow for social and meaningful actions’ data to
follow a learning object through its life cycle. When different
versions or formats have special features or specific
rights’ stipulations, these can also be effectively
expressed all in one metadata container.

Conclusion

This paper presented the IMS LODE Information
for Learning Object eXchange (ILOX) data model, a framework for
organizing, in a semantically meaningful way, multiple metadata
specifications in one container. ILOX is a generic framework that
can potentially be used to organize metadata about any kind of
resources.

This framework facilitates the collection and
handling of the diverse information necessary to efficiently
retrieve learning objects. It allows for the processing of all
the metadata about a resource as an entirety and for integrating
in one container all of the appropriate
specifications.

This framework is being developed as part of
the Learning Object Discovery & Exchange (LODE) specification
[5] of the IMS Global Learning Consortium
[13] with the support of the ASPECT project [14] that used ILOX
as a basis for producing a new version of the LRE Metadata
Application Profile. The latter makes it possible to easily
manage the discovery and exchange of learning resources in
multiple formats and versions.

It is important to note that because ILOX is a
framework for organizing metadata rather than a new metadata
specification, it was possible to completely automate the
generation of ILOXes from existing metadata records thus easing
the adoption of the new LRE application profile by the LRE
content providers.

Taking advantage of the experience gained with
the LRE metadata application profile, the IMS LODE group is now
working on an IMS profile of ILOX for learning objects. We expect
this profile to be ready by February
2011.

Acknowledgments

The work presented in this paper is partially
supported by the European Community eContentplus programme
- project ASPECT: Adopting Standards and Specifications for
Educational Content (Grant agreement number ECP-2007-EDU-417008).
The authors are solely responsible for the content of this paper.
It does not represent the opinion of the European Community and
the European Community is not responsible for any use that might
be made of information contained
therein.

1 Alternative initiatives to provide a
description framework for usage data include CEN/ISSS work on
social data [12] and NSDL work on
paradata.

2 “Information modeling is concerned
with the construction of computer-based symbol structures which
capture the meaning of information and organize it in ways that
make it understandable and useful to people.”
[9]

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